Recurrent focal segmental glomerulosclerosis in the renal allograft: single center experience in the era of modern immunosuppression
Bibliographic record
Abstract
FSGS is an important cause of ESRD and tends to recur in allografts (rFSGS). Older series suggest recurrence rates of 30-60%. In the modern era of transplant immunosuppression, recurrence rates are unknown. There are also few data regarding prevalence of known genetic mutations in adult FSGS patients who undergo transplantation. Recently, FSGS has been subdivided into histological variants, which may predict renal outcomes; there is little information on patterns of recurrence and outcomes in these variants. Finally, treatment for rFSGS relies upon up-titrating calcineurin inhibitors and plasmapheresis. Insufficient information exists on the use of these regimens for rFSGS in the era of modern immunosuppression. We conducted a retrospective chart review involving all renal transplant recipients at Columbia University Medical Center from December 1999 to March 2007. Those with biopsy confirmed primary FSGS were included and information regarding baseline characteristics, histologic variants, genetics, treatment, and clinical outcomes were collected. FSGS recurred in 23% of patients. Those with collapsing histology on native kidney biopsy, tended to recur with the same histology. No known genetic mutations were identified among those with recurrence. Plasmapheresis resulted in complete or partial remission in 75% of those with recurrence. Recurrent FSGS resulted in a trend toward the combined outcome of ESRD or death compared to those without recurrence (27% vs. 12%). Modern immunosuppression does not reduce the rate of rFSGS, known genetic mutations are uncommon in such adult patients, collapsing FSGS tends to recur with the same histology, and plasmapheresis may be helpful in the treatment of recurrence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".